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Published February 2023 | Published + Supplemental Material
Journal Article Open

Constraining CaCO₃ Export and Dissolution With an Ocean Alkalinity Inverse Model

Abstract

Ocean alkalinity plays a fundamental role in the apportionment of CO₂ between the atmosphere and the ocean. The primary driver of the ocean's vertical alkalinity distribution is the formation of calcium carbonate (CaCO₃) by organisms at the ocean surface and its dissolution at depth. This so-called "CaCO₃ counterpump" is poorly constrained, however, both in terms of how much CaCO₃ is exported from the surface ocean, and at what depth it dissolves. Here, we created a steady-state model of global ocean alkalinity using Ocean Circulation Inverse Model transport, biogeochemical cycling, and field-tested calcite and aragonite dissolution kinetics. We find that limiting CaCO₃ dissolution to below the aragonite and calcite saturation horizons cannot explain excess alkalinity in the upper ocean, and that models allowing dissolution above the saturation horizons best match observations. Linking dissolution to organic matter respiration, or imposing a constant dissolution rate both produce good model fits. Our best performing models require export between 1.1 and 1.8 Gt PIC y⁻¹ (from 73 m), but all converge to 1.0 Gt PIC y⁻¹ export at 279 m, indicating that both high- and low-export scenarios can match observations, as long as high export is coupled to high dissolution in the upper ocean. These results demonstrate that dissolution is not a simple function of seawater CaCO₃ saturation (Ω) and calcite or aragonite solubility, and that other mechanisms, likely related to the biology and ecology of calcifiers, must drive significant dissolution throughout the water column.

Additional Information

© 2023. The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. This research was supported by funding from the National Science Foundation to W.B. (OCE 1834475) and S.J. (OCE 2049639); by the Simons Foundation to S.J. (SCOPE Award 329108); and by the University of Southern California Dornsife College of Letters, Arts, and Sciences, and Provost Fellowship to A.L. The authors wish to thank Brendan Carter for sharing preformed alkalinity data and Thomas Weber for sharing PIC:POC data. Hengdi Liang and Abby M. Lunstrum contributed equally to this work. Data Availability Statement. The original modeling tool AWESOME OCIM (John et al., 2020) used in this study is published on GitHub at: https://github.com/MTEL-USC/AWESOME-OCIM. The observations of total alkalinity, salinity, nitrate, phosphate, calcite omega, and aragonite omega have been pre-loaded in AWESOME OCIM, but are originally from the GLODAP version 2 mapped data product (Lauvset et al., 2016) available at: https://www.glodap.info/index.php/mapped-data-product/. The riverine alkalinity data were compiled from Table 6 in Amiotte-Suchet et al. (2003). The data used for calculating alkalinity burial in the open ocean and coastal areas are downloadable from the Supporting Information of Dunne et al. (2012) and O'Mara and Dunne (2019), respectively. The preformed alkalinity data and calculation method are from Carter et al. (2021), archived via Zenodo: https://doi.org/10.5281/zenodo.3745002. All external data have been re-gridded and pre-loaded in our model and uploaded together with the MATLAB codes and model outputs to the Zenodo repository at: https://doi.org/10.5281/zenodo.7502884.

Attached Files

Published - Global_Biogeochemical_Cycles_-_2023_-_Liang_-_Constraining_CaCO3_Export_and_Dissolution_With_an_Ocean_Alkalinity_Inverse.pdf

Supplemental Material - 2022gb007535-sup-0001-supporting_information_si-s01.docx

Files

Global_Biogeochemical_Cycles_-_2023_-_Liang_-_Constraining_CaCO3_Export_and_Dissolution_With_an_Ocean_Alkalinity_Inverse.pdf

Additional details

Created:
August 22, 2023
Modified:
October 23, 2023